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At least 757 records · Page 42

Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist

We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We also demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.

59 BASIC BIOLOGICAL SCIENCES↗

Path-integral and Ornstein-Zernike study of quantum fluid structures on the crystallization line

Liquid neon, liquid para-hydrogen, and the quantum hard-sphere fluid are studied with path integral Monte Carlo simulations and the Ornstein-Zernike pair equation on their respective crystallization lines. The results cover the whole sets of structures in the r-space and the k-space and, for completeness, the internal energies, pressures and isothermal compressibilities. Comparison with experiment is made wherever possible, and the possibilities of establishing k-space criteria for quantum crystallization based on the path-integral centroids are discussed. In this regard, the results show that the centroid structure factor contains two significant parameters related to its main peak features (amplitude and shape) that can be useful to characterize freezing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ASCR/HEP Exascale Requirements Review Report

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.

97 MATHEMATICS AND COMPUTING↗

ASCR/HEP Exascale Requirements Review Report

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.

Habib, Salman↗

Nuclear Quantum Effects on the Electronic Structure of Water and Ice

The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of the hydrogen atoms. Despite numerous previous studies, a comprehensive understanding of the nuclear quantum effects (NQEs) on the electronic structure of water and ice at finite temperatures remains elusive. Here, we utilize molecular simulations that harness efficient machine-learning potentials and many-body perturbation theory to assess how NQEs impact the electronic bands of water and hexagonal ice. By comparing path-integral and classical simulations, we find that NQEs lead to a larger renormalization of the fundamental gap of ice, compared to that of water, ultimately yielding similar bandgaps in the two systems, consistent with experimental estimates. Our calculations suggest that the increased quantum mechanical delocalization of protons in ice, relative to water, is a key factor leading to the enhancement of NQEs on the electronic structure of ice.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monthly hydropower generation data for Western Canada to support Western-US interconnect power system studies

Hydroelectric power generation in Western Canada significantly contributes to power grid operations of the North American Western Interconnection through substantial generation, some of which is exported to the United States (U.S.). However, the lack of publicly available hydropower generation datasets poses challenges for future market projections and resource adequacy evaluations. We present a simulation-based monthly power system model-ready hydropower generation dataset for 110 facilities in British Columbia and Alberta from 1981 to 2019. These monthly hydropower generation estimates are developed from integrated hydrologic model simulations of runoff and reservoir-operated streamflow, followed by scaling that considers diversion inflow constraints based on hydropower water license information. To address the lack of comparable hydropower generation records, we conduct step-by-step evaluations for simulated runoff, regulated streamflow, and hydropower generation using available observations or estimates. The presented hydropower dataset aims to enhance the representation of hydropower resources in Western Canada, supporting power grid system studies for the Western Interconnection of the U.S. and Canada.

13 HYDRO ENERGY↗

Fundamental Advancements in Pre-Chamber Spark Ignition and Emissions Control for Natural Gas Engines

Argonne National Laboratory, the National Renewable Energy Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories collaborated on research to address barriers for natural gas engine efficiency. This research project focuses on early stage research focusing on pre-chamber spark-ignition (PCSI) to achieve diesel-like efficiency in medium- and heavy-duty natural gas engines by extending the lean dilution limit and/or exhaust gas recirculation (EGR) dilution limit, as well as shortening burn duration, with integrated aftertreatment. This project integrates experimental and simulation based tasks to address four key barriers to market penetration of PCSI for medium- and heavy-duty natural gas engines. These include Inadequate science base and simulation tools to describe/predict the fluid-mechanical and chemical-kinetic processes governing PCSI to enable engineers in industry to optimize designs for efficiency, noise, reliability, pollutant formation, emissions control integration, and drivability; limited ability to extend EGR and/or lean dilution limits at higher loads; increased propensity for PCSI hot-spot pre-ignition at high loads relative to spark ignition; and ineffective methane catalysts for the high engine-out unburned fuel concentrations coupled with low exhaust temperatures (<<400 degrees C) of high efficiency engines.

33 ADVANCED PROPULSION SYSTEMS↗

Optimized Lie–Trotter–Suzuki decompositions for two and three non-commuting terms

Lie–Trotter–Suzuki decompositions are an efficient way to approximate operator exponentials exp ( t H ) when H is a sum of n (non-commuting) terms which, individually, can be exponentiated easily. They are employed in time-evolution algorithms for tensor network states, digital quantum simulation protocols, path integral methods like quantum Monte Carlo, and splitting methods for symplectic integrators in classical Hamiltonian systems. Here, we provide optimized decompositions up to order t 6 . The leading error term is expanded in nested commutators (Hall bases) and we minimize the 1-norm of the coefficients. For n = 2 terms, several of the optima we find are close to those in McLachlan (1995). Generally, our results substantially improve over unoptimized decompositions by Forest, Ruth, Yoshida, and Suzuki. We explain why these decompositions are sufficient to efficiently simulate any one- or two-dimensional lattice model with finite-range interactions. This follows by solving a partitioning problem for the interaction graph.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

FUEL PERFORMANCE SIMULATION OF HIGH BURNUP FUELS IN PLANNED INTEGRAL DESIGN BASIS ACCIDENT EXPERIMENTS

High burnup (HBu) fuel rods from the Byron Nuclear Generating Station (BNGS) were recently received at Idaho National Laboratory (INL) to support a variety of planned Nuclear Energy fuel cycle R&D objectives ranging from fuel performance, fuel recycle, and spent fuel research topics. Among these R&D activities, these fuel rods will be the subjects of multiple in-pile experiment programs at the Transient Reactor Test (TREAT) facility as well as detailed characterization and testing in the hot cells at INL and Oak Ridge National Laboratory (ORNL). TREAT RIA experiments are planned for the Nuclear Energy Agency Framework for Irradiation Experiments (FIDES) Joint Experimental Program called High burnup Experiments in Reactivity Initiated Accident (HERA) program. TREAT and ORNL-furnace LOCA experiments are part of the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program U.S. consensus LOCA test plan, and the in-pile experiments have also been proposed in a FIDES project called Loss of Coolant-High Burnup (LOC-HBu). The results of these test programs will provide crucial data about safety performance enabling extended licensable burnup limits for these fuels. The purpose of this paper is to document fuel performance computational simulations of the BNGS fuel using the Bison code. The detailed assessments include (1) the irradiation history of the fuel to provide prediction of as-run fuel conditions and (2) extending the irradiated fuel conditions into the as-designed experiment conditions for the HERA-HBu RIA experiments and for the LOC-HBu LOCA experiments. The results of these assessments will inform post-irradiation examinations (PIE) of the BNGS parent rods and detailed final design of the planned experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FUEL PERFORMANCE SIMULATION OF HIGH BURNUP FUELS IN PLANNED INTEGRAL DESIGN BASIS ACCIDENT EXPERIMENTS

High burnup (HBu) fuel rods from the Byron Nuclear Generating Station (BNGS) were recently received at Idaho National Laboratory (INL) to support a variety of planned Nuclear Energy fuel cycle R&D objectives ranging from fuel performance, fuel recycle, and spent fuel research topics. Among these R&D activities, these fuel rods will be the subjects of multiple in-pile experiment programs at the Transient Reactor Test (TREAT) facility as well as detailed characterization and testing in the hot cells at INL and Oak Ridge National Laboratory (ORNL). TREAT RIA experiments are planned for the Nuclear Energy Agency Framework for Irradiation Experiments (FIDES) Joint Experimental Program called High burnup Experiments in Reactivity Initiated Accident (HERA) program. TREAT and ORNL-furnace LOCA experiments are part of the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program U.S. consensus LOCA test plan, and the in-pile experiments have also been proposed in a FIDES project called Loss of Coolant-High Burnup (LOC-HBu). The results of these test programs will provide crucial data about safety performance enabling extended licensable burnup limits for these fuels. The purpose of this paper is to document fuel performance computational simulations of the BNGS fuel using the Bison code. The detailed assessments include (1) the irradiation history of the fuel to provide prediction of as-run fuel conditions and (2) extending the irradiated fuel conditions into the as-designed experiment conditions for the HERA-HBu RIA experiments and for the LOC-HBu LOCA experiments. The results of these assessments will inform post-irradiation examinations (PIE) of the BNGS parent rods and detailed final design of the planned experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fuel Performance Simulation of High Burnup Fuels in Planned Integral Design Basis Accident Experiments

High burnup (HBu) fuel rods from the Byron Nuclear Generating Station (BNGS) were recently received at Idaho National Laboratory (INL) to support a variety of planned Nuclear Energy fuel cycle R&D objectives ranging from fuel performance, fuel recycle, and spent fuel research topics. Among these R&D activities, these fuel rods will be the subjects of multiple in-pile experiment programs at the Transient Reactor Test (TREAT) facility as well as detailed characterization and testing in the hot cells at INL and Oak Ridge National Laboratory (ORNL). TREAT RIA experiments are planned for the Nuclear Energy Agency Framework for Irradiation Experiments (FIDES) Joint Experimental Program called High burnup Experiments in Reactivity Initiated Accident (HERA) program. TREAT and ORNL-furnace LOCA experiments are part of the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program U.S. consensus LOCA test plan, and the in-pile experiments have also been proposed in a FIDES project called Loss of Coolant-High Burnup (LOC-HBu). The results of these test programs will provide crucial data about safety performance enabling extended licensable burnup limits for these fuels. The purpose of this paper is to document fuel performance computational simulations of the BNGS fuel using the Bison code. The detailed assessments include (1) the irradiation history of the fuel to provide prediction of as-run fuel conditions and (2) extending the irradiated fuel conditions into the as-designed experiment conditions for the HERA-HBu RIA experiments and for the LOC-HBu LOCA experiments. The results of these assessments will inform post-irradiation examinations (PIE) of the BNGS parent rods and detailed final design of the planned experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Fully Explicit Integrator for Modeling Astrophysical Reactive Flows

Simulating complex astrophysical reacting flows is computationally expensive—reactions are stiff and typically require implicit integration methods. The reaction update is often the most expensive part of a simulation, which motivates the exploration of more economical methods. In this research note, we investigate how the explicit Runge–Kutta–Chebyshev (RKC) method performs compared to an implicit method when applied to astrophysical reactive flows. These integrators are applied to simulations of X-ray bursts arising from unstable thermonuclear burning of accreted fuel on the surface of neutron stars. We show that the RKC method performs with similar accuracy to our traditional implicit integrator, but is more computationally efficient when run on CPUs.

GPU computing↗

Modeling, Validation, and Control of the IEA‐15 MW Reference Wind Turbine and VolturnUS‐S Platform

This paper presents the acausal modeling, validation, and control of floating offshore wind turbines (FOWTs). The model simulates the IEA‐15 MW reference turbine and the semi‐submersible VolturnUS‐S platform utilizing a Control‐oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS), which integrates the key coupled aero‐hydro‐elasto‐servo dynamics and is being developed by authors at the University of Central Florida. Verification and validation are conducted using numerical data from the industry‐standard simulation platform OpenFAST and experimental data from the Floating Offshore‐wind and Controls Advanced Laboratory (FOCAL) project, in which the authors were involved. Numerical results demonstrate the model's ability to qualitatively capture loads and responses across various load cases, highlighting the impact of the control system under different wind and wave conditions and opening new opportunities for optimizing FOWT designs. This paper provides wind turbine researchers with valuable insights into system characteristics, system frequencies, damping effects, and internal reaction forces, serving as a reference for future studies in FOWT modeling and control.

17 WIND ENERGY↗

A hydrological simulation dataset of the Upper Colorado River Basin from 1983 to 2019

Abstract This article presents a hydrological reconstruction of the Upper Colorado River Basin with an hourly temporal resolution, and 1-km spatial resolution from October 1982 to September 2019. The validated dataset includes a suite of hydrologic variables including streamflow, water table depth, snow water equivalent (SWE) and evapotranspiration (ET) simulated by an integrated hydrological model, ParFlow-CLM. The dataset was validated over the period with a combination of point observations and remotely sensed products. These datasets provide a long-term, natural-flow, simulation for one of the most over-allocated basins in the world.

54 ENVIRONMENTAL SCIENCES↗

Internet-of-Things Hardware-in-the-Loop Simulation Architecture for Providing Frequency Regulation With Demand Response

Following recent advances in network infrastructure, cloud computing, and embedded systems, fascinating work is underway exploring the utility of demand response in increasing grid stability while permitting high penetration of intermittent renewable distributed generation resources. Although works have demonstrated diverse theoretical advantages of demand response programs, little real-world data are available and utilities generally remain reticent in moving forward with large-scale implementation due to risks inherent to any modification of the power system. Deciding that the next pertinent step in bringing demand response from theory to technology is developing an Internet-of-things hardware-in-the-loop simulation power system integrated device capable of empirically testing the theoretical mechanisms, this work presents an architecture testbed for providing demand response (telemetric monitoring and actuation of loads), which is real node in a power system simulation where virtual node's parameters derive real node data. Finally, we test a demand response algorithm, which provides frequency regulation services.

97 MATHEMATICS AND COMPUTING↗

A simulation framework for evaluating electronic order workflows in integrated health records

Electronic health record (EHR) systems are critical to modern healthcare delivery, yet the dynamic workflows that govern electronic order processing remain underexplored. Inefficiencies in these digital pathways can cause delays in care, repetitive workloads, and even patient harm. This study presents a discrete-event simulation framework used to reconstruct and evaluate EHR-based order workflows in a large integrated healthcare system. Using real-world data extracted from the Veterans Health Administration’s Corporate Data Warehouse, the authors mapped order events to standardized state transitions and modeled their progression across different facilities of varying complexity levels. After being calibrated with empirical distributions of transition times and validated against observed time-in-system metrics, the simulation demonstrates close alignment with historical performance. Scenario analyses reveal that resource capacity constraints significantly amplify the impact of electronic order surges, which are reflected in the disproportionate growth in backlogs and processing delays. Adjustments in transition probabilities further increased recirculation and extended workflow paths. Network-based analysis identified Reserved, InProgress, and Completed as structurally critical states that function as hubs within the process network but the transitions in-between also act as major bottlenecks. These results showcased the effectiveness of simulation-based approaches in monitoring EHR order processing performance and evaluating consequences of workflow changes on healthcare network resources planning. The proposed simulation framework provides a scalable data-driven tool to support operational decision-making and improve the efficiency of electronic order management in complex healthcare environments.

Engineering↗

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗

On Design of a Coupling Component for Parallel Multimodeling

A component-based simulation framework is a favorable choice for many multi-scale simulations, which requires dedicated coupling to support flexible data communication/exchange between components, computational parallelism and on-demand dynamic load balancing. In this paper, authors first present the considerations in the course of design and implementation of a coupling component to support integrated parallel multimodeling. Then, authors use an integrated ecological modeling case, as a part of the Across Trophic Level System Simulation (ATLSS) for the ecological restoration projects in the Everglades of South Florida, to demonstrate the practical application of such component in real-world simulations. In the case study, we illustrated the internal data flow between the ecological models and the performance enhancement of the integrated simulation via the coupling component.

99 GENERAL AND MISCELLANEOUS↗